Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add karellen/karellen-rr-mcp --skill rr-debug-racegit clone --depth 1 https://github.com/karellen/karellen-rr-mcpWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/karellen/karellen-rr-mcp/rr-debug-race)<a href="https://agentmods.dev/skills/karellen/karellen-rr-mcp/rr-debug-race"><img src="https://agentmods.dev/badge/skills/karellen/karellen-rr-mcp/rr-debug-race/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/karellen/karellen-rr-mcp/rr-debug-race"><img src="https://agentmods.dev/badge/skills/karellen/karellen-rr-mcp/rr-debug-race.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00036 | $0.00852 |
| Opus 5 | $0.00018 | $0.00426 |
| Sonnet 5 | $0.00007 | $0.00170 |
| Haiku 4.5 | $0.00004 | $0.00085 |
Grade A, and why
rr-debug-race scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 139 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Debug Data Race with rr
Use this skill when you suspect a data race, deadlock, or concurrency bug. rr records the exact thread interleaving that occurred, then replays it deterministically so you can inspect every thread's state at every point.
Why rr for Concurrency Bugs
- Races are non-deterministic — they may not reproduce on re-run. rr captures the exact interleaving and replays it identically every time.
- You can inspect all threads at any point in the execution.
- Watchpoints + reverse execution let you trace a corrupted value back to the exact write from the racing thread.
Workflow
1. Record the Failure
Run the program under rr. If the race is intermittent, you may need multiple attempts:
rr_record(command=$ARGUMENTS, trace_dir="<project>/rr-trace-<random>")
For sanitizer-detected races, enable ThreadSanitizer to make the race more visible:
rr_record(command=["./program"], env={"TSAN_OPTIONS": "halt_on_error=1"}, trace_dir=...)
2. Start Replay
rr_ps(trace_dir="<trace>")
rr_replay_start(trace_dir="<trace>", pid=<pid>)
3. Survey the Threads
Before diving in, understand the thread landscape:
rr_continue()
At the crash or end point:
rr_thread_list()
Note which threads exist and their states. Switch between threads to see what each was doing:
rr_thread_select(<tid>)
rr_backtrace()
rr_locals()
4. Find the Contested Data
Identify the shared variable or memory that is being raced on. This might be obvious from the crash (e.g., corrupted pointer) or from sanitizer output.
Set a watchpoint on the contested data:
rr_watchpoint_set("shared_variable")
Or on a memory address:
rr_watchpoint_set("*(int*)0x7fff5678")
5. Trace All Accesses
Use continue (forward and reverse) to find every access to the contested data:
rr_continue() # Find the next write
rr_backtrace() # Who wrote it?
rr_thread_list() # Which thread?
Save checkpoints at each access point:
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 12d ago First seen · 139 lines · 36 tokens per session scan A 68672d37c1f9
rr-debug-race is a skill published in the GitHub repository karellen/karellen-rr-mcp (3 stars, last pushed 4mo ago), licensed Apache-2.0. It adds 36 tokens to every session and 852 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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